format code, test=doc

paddlespeech/server/bin/main.py

@@ -12,8 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import argparse
+
 import uvicorn
-import yaml
 from fastapi import FastAPI
 
 from paddlespeech.server.engine.engine_pool import init_engine_pool

paddlespeech/server/bin/paddlespeech_client.py

@@ -124,7 +124,7 @@ class TTSClientExecutor(BaseExecutor):
             logger.info("RTF: %f " % (time_consume / duration))
 
             return True
-        except:
+        except BaseException:
             logger.error("Failed to synthesized audio.")
             return False
 
@@ -164,7 +164,7 @@ class TTSClientExecutor(BaseExecutor):
             print("Audio duration: %f s." % (duration))
             print("Response time: %f s." % (time_consume))
             print("RTF: %f " % (time_consume / duration))
-        except:
+        except BaseException:
             print("Failed to synthesized audio.")
 
 
@@ -211,7 +211,7 @@ class ASRClientExecutor(BaseExecutor):
             logger.info(r.json())
             logger.info("time cost %f s." % (time_end - time_start))
             return True
-        except:
+        except BaseException:
             logger.error("Failed to speech recognition.")
             return False
 
@@ -242,5 +242,5 @@ class ASRClientExecutor(BaseExecutor):
             time_end = time.time()
             print(r.json())
             print("time cost %f s." % (time_end - time_start))
-        except:
+        except BaseException:
             print("Failed to speech recognition.")

paddlespeech/server/engine/asr/paddleinference/asr_engine.py

@@ -13,31 +13,24 @@
 # limitations under the License.
 import io
 import os
-from typing import List
 from typing import Optional
-from typing import Union
 
-import librosa
 import paddle
-import soundfile
 from yacs.config import CfgNode
 
-from paddlespeech.cli.utils import MODEL_HOME
-from paddlespeech.s2t.modules.ctc import CTCDecoder
 from paddlespeech.cli.asr.infer import ASRExecutor
 from paddlespeech.cli.log import logger
+from paddlespeech.cli.utils import MODEL_HOME
 from paddlespeech.s2t.frontend.featurizer.text_featurizer import TextFeaturizer
-from paddlespeech.s2t.transform.transformation import Transformation
-from paddlespeech.s2t.utils.dynamic_import import dynamic_import
+from paddlespeech.s2t.modules.ctc import CTCDecoder
 from paddlespeech.s2t.utils.utility import UpdateConfig
+from paddlespeech.server.engine.base_engine import BaseEngine
 from paddlespeech.server.utils.config import get_config
 from paddlespeech.server.utils.paddle_predictor import init_predictor
 from paddlespeech.server.utils.paddle_predictor import run_model
-from paddlespeech.server.engine.base_engine import BaseEngine
 
 __all__ = ['ASREngine']
 
-
 pretrained_models = {
     "deepspeech2offline_aishell-zh-16k": {
         'url':
@@ -143,7 +136,6 @@ class ASRServerExecutor(ASRExecutor):
             batch_average=True,  # sum / batch_size
             grad_norm_type=self.config.get('ctc_grad_norm_type', None))
 
-
     @paddle.no_grad()
     def infer(self, model_type: str):
         """
@@ -161,9 +153,8 @@ class ASRServerExecutor(ASRExecutor):
                 cfg.beam_size, cfg.cutoff_prob, cfg.cutoff_top_n,
                 cfg.num_proc_bsearch)
 
-            output_data = run_model(
-                                self.am_predictor,
-                                [audio.numpy(), audio_len.numpy()])
+            output_data = run_model(self.am_predictor,
+                                    [audio.numpy(), audio_len.numpy()])
 
             probs = output_data[0]
             eouts_len = output_data[1]
@@ -208,14 +199,14 @@ class ASREngine(BaseEngine):
 
         paddle.set_device(paddle.get_device())
         self.executor._init_from_path(
-                    model_type=self.config.model_type,
-                    am_model=self.config.am_model,
-                    am_params=self.config.am_params,
-                    lang=self.config.lang,
-                    sample_rate=self.config.sample_rate,
-                    cfg_path=self.config.cfg_path,
-                    decode_method=self.config.decode_method,
-                    am_predictor_conf=self.config.am_predictor_conf)
+            model_type=self.config.model_type,
+            am_model=self.config.am_model,
+            am_params=self.config.am_params,
+            lang=self.config.lang,
+            sample_rate=self.config.sample_rate,
+            cfg_path=self.config.cfg_path,
+            decode_method=self.config.decode_method,
+            am_predictor_conf=self.config.am_predictor_conf)
 
         logger.info("Initialize ASR server engine successfully.")
         return True
@@ -230,7 +221,8 @@ class ASREngine(BaseEngine):
                 io.BytesIO(audio_data), self.config.sample_rate,
                 self.config.force_yes):
             logger.info("start running asr engine")
-            self.executor.preprocess(self.config.model_type, io.BytesIO(audio_data))
+            self.executor.preprocess(self.config.model_type,
+                                     io.BytesIO(audio_data))
             self.executor.infer(self.config.model_type)
             self.output = self.executor.postprocess()  # Retrieve result of asr.
             logger.info("end inferring asr engine")

paddlespeech/server/engine/base_engine.py

@@ -12,8 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import os
-from typing import Any
-from typing import List
 from typing import Union
 
 from pattern_singleton import Singleton

paddlespeech/server/engine/engine_factory.py

@@ -13,7 +13,6 @@
 # limitations under the License.
 from typing import Text
 
-
 __all__ = ['EngineFactory']
 
 

paddlespeech/server/engine/engine_pool.py

@@ -29,8 +29,10 @@ def init_engine_pool(config) -> bool:
     """
     global ENGINE_POOL
     for engine in config.engine_backend:
-        ENGINE_POOL[engine] = EngineFactory.get_engine(engine_name=engine, engine_type=config.engine_type[engine])
-        if not ENGINE_POOL[engine].init(config_file=config.engine_backend[engine]):
+        ENGINE_POOL[engine] = EngineFactory.get_engine(
+            engine_name=engine, engine_type=config.engine_type[engine])
+        if not ENGINE_POOL[engine].init(
+                config_file=config.engine_backend[engine]):
             return False
 
     return True

paddlespeech/server/engine/tts/paddleinference/tts_engine.py

@@ -360,8 +360,8 @@ class TTSEngine(BaseEngine):
                 am_predictor_conf=self.config.am_predictor_conf,
                 voc_predictor_conf=self.config.voc_predictor_conf, )
 
-        except:
-            logger.info("Initialize TTS server engine Failed.")
+        except BaseException:
+            logger.error("Initialize TTS server engine Failed.")
             return False
 
         logger.info("Initialize TTS server engine successfully.")
@@ -405,11 +405,13 @@ class TTSEngine(BaseEngine):
         # transform speed
         try:  # windows not support soxbindings
             wav_speed = change_speed(wav_vol, speed, target_fs)
-        except:
+        except ServerBaseException:
             raise ServerBaseException(
                 ErrorCode.SERVER_INTERNAL_ERR,
                 "Transform speed failed. Can not install soxbindings on your system. \
                  You need to set speed value 1.0.")
+        except BaseException:
+            logger.error("Transform speed failed.")
 
         # wav to base64
         buf = io.BytesIO()
@@ -462,9 +464,11 @@ class TTSEngine(BaseEngine):
         try:
             self.executor.infer(
                 text=sentence, lang=lang, am=self.config.am, spk_id=spk_id)
-        except:
+        except ServerBaseException:
             raise ServerBaseException(ErrorCode.SERVER_INTERNAL_ERR,
                                       "tts infer failed.")
+        except BaseException:
+            logger.error("tts infer failed.")
 
         try:
             target_sample_rate, wav_base64 = self.postprocess(
@@ -474,8 +478,10 @@ class TTSEngine(BaseEngine):
                 volume=volume,
                 speed=speed,
                 audio_path=save_path)
-        except:
+        except ServerBaseException:
             raise ServerBaseException(ErrorCode.SERVER_INTERNAL_ERR,
                                       "tts postprocess failed.")
+        except BaseException:
+            logger.error("tts postprocess failed.")
 
         return lang, target_sample_rate, wav_base64

paddlespeech/server/engine/tts/python/tts_engine.py

@@ -72,8 +72,8 @@ class TTSEngine(BaseEngine):
                 voc_ckpt=self.config.voc_ckpt,
                 voc_stat=self.config.voc_stat,
                 lang=self.config.lang)
-        except:
-            logger.info("Initialize TTS server engine Failed.")
+        except BaseException:
+            logger.error("Initialize TTS server engine Failed.")
             return False
 
         logger.info("Initialize TTS server engine successfully.")
@@ -117,10 +117,13 @@ class TTSEngine(BaseEngine):
         # transform speed
         try:  # windows not support soxbindings
             wav_speed = change_speed(wav_vol, speed, target_fs)
-        except:
+        except ServerBaseException:
             raise ServerBaseException(
                 ErrorCode.SERVER_INTERNAL_ERR,
-                "Can not install soxbindings on your system.")
+                "Transform speed failed. Can not install soxbindings on your system. \
+                 You need to set speed value 1.0.")
+        except BaseException:
+            logger.error("Transform speed failed.")
 
         # wav to base64
         buf = io.BytesIO()
@@ -173,9 +176,11 @@ class TTSEngine(BaseEngine):
         try:
             self.executor.infer(
                 text=sentence, lang=lang, am=self.config.am, spk_id=spk_id)
-        except:
+        except ServerBaseException:
             raise ServerBaseException(ErrorCode.SERVER_INTERNAL_ERR,
                                       "tts infer failed.")
+        except BaseException:
+            logger.error("tts infer failed.")
 
         try:
             target_sample_rate, wav_base64 = self.postprocess(
@@ -185,8 +190,10 @@ class TTSEngine(BaseEngine):
                 volume=volume,
                 speed=speed,
                 audio_path=save_path)
-        except:
+        except ServerBaseException:
             raise ServerBaseException(ErrorCode.SERVER_INTERNAL_ERR,
                                       "tts postprocess failed.")
+        except BaseException:
+            logger.error("tts postprocess failed.")
 
         return lang, target_sample_rate, wav_base64

paddlespeech/server/restful/asr_api.py

@@ -14,6 +14,7 @@
 import base64
 import traceback
 from typing import Union
+
 from fastapi import APIRouter
 
 from paddlespeech.server.engine.engine_pool import get_engine_pool
@@ -83,7 +84,7 @@ def asr(request_body: ASRRequest):
 
     except ServerBaseException as e:
         response = failed_response(e.error_code, e.msg)
-    except:
+    except BaseException:
         response = failed_response(ErrorCode.SERVER_UNKOWN_ERR)
         traceback.print_exc()
 

paddlespeech/server/restful/request.py

@@ -11,7 +11,6 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import List
 from typing import Optional
 
 from pydantic import BaseModel

paddlespeech/server/restful/response.py

@@ -11,9 +11,6 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import List
-from typing import Optional
-
 from pydantic import BaseModel
 
 __all__ = ['ASRResponse', 'TTSResponse']

paddlespeech/server/restful/tts_api.py

@@ -114,7 +114,7 @@ def tts(request_body: TTSRequest):
         }
     except ServerBaseException as e:
         response = failed_response(e.error_code, e.msg)
-    except:
+    except BaseException:
         response = failed_response(ErrorCode.SERVER_UNKOWN_ERR)
         traceback.print_exc()
 

paddlespeech/server/tests/asr/http_client.py

@@ -10,11 +10,11 @@
 # distributed under the License is distributed on an "AS IS" BASIS,
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the 
-import requests
+import base64
 import json
 import time
-import base64
-import io
+
+import requests
 
 
 def readwav2base64(wav_file):
@@ -34,23 +34,23 @@ def main():
     url = "http://127.0.0.1:8090/paddlespeech/asr"
 
     # start Timestamp
-    time_start=time.time()
+    time_start = time.time()
 
     test_audio_dir = "./16_audio.wav"
     audio = readwav2base64(test_audio_dir)
 
     data = {
-            "audio": audio,
-            "audio_format": "wav",
-            "sample_rate": 16000,
-            "lang": "zh_cn",
-            }
+        "audio": audio,
+        "audio_format": "wav",
+        "sample_rate": 16000,
+        "lang": "zh_cn",
+    }
 
     r = requests.post(url=url, data=json.dumps(data))
 
     # ending Timestamp
-    time_end=time.time()
-    print('time cost',time_end - time_start, 's')
+    time_end = time.time()
+    print('time cost', time_end - time_start, 's')
 
     print(r.json())
 

paddlespeech/server/tests/tts/test_client.py

@@ -25,6 +25,7 @@ import soundfile
 
 from paddlespeech.server.utils.audio_process import wav2pcm
 
+
 # Request and response
 def tts_client(args):
     """ Request and response
@@ -99,5 +100,5 @@ if __name__ == "__main__":
         print("Inference time: %f" % (time_consume))
         print("The duration of synthesized audio: %f" % (duration))
         print("The RTF is: %f" % (rtf))
-    except:
+    except BaseException:
         print("Failed to synthesized audio.")

paddlespeech/server/util.py

@@ -219,7 +219,7 @@ class ConfigCache:
             try:
                 cfg = yaml.load(file, Loader=yaml.FullLoader)
                 self._data.update(cfg)
-            except:
+            except BaseException:
                 self.flush()
 
     @property